Marketers today bring in traffic through various channels and as the internet world grows, we will see many new ways of reaching out to potential customer. In doing so, we have also realized the importance of measuring the effectiveness of campaigns and taking it one step further, we are also able to see the customer's journey from its first touch point to conversion.

Since users can reach your website through various channels, it is important to set up a system for allocating credit to the channels that contributed to conversion. Users can come in through multiple channels and might only convert in one of those visits. Attribution models such as 'Last Touch', 'First Touch', 'Time Decay', etc. are some of the popular models used for allocating credit to channels.

But the question is, are these attribution models able to paint a clear picture of a customer's journey to conversion?

The answer is "Not Really".

We will discuss this in more detail in the analysis recipe section to see how Campaign Stacking plays a crucial role in understanding a customer's journey and allocating credit to the set of channels.

Analysis Overview:

This article provides a concrete understanding of Campaign Stacking and how it can be implemented. Since Campaign Stacking is native to Adobe Analytics due to cross-visitation plug-in, we have also provided a work-around in Google Analytics.

Analysis Benefits:

Using Campaign Stacking, we can answer some of the below mentioned questions –

What are some of the common channel combinations users engage with before converting?

Which channel combinations contribute the most to revenue, orders, etc.?

Please note, this tool can be used much beyond the world of campaigns.

We can also apply the same logic to see which products people viewed before converting or sections and tools of the website that users tend to interact with before converting.

The possibilities are endless and once you have understood how Campaign Stacking works, it can become a powerful tool deployed in the form of a report.